Bearing fault diagnosis method based on multi-island inheritance and variational mode decomposition

Abstract

The invention provides a bearing fault diagnosis method based on multi-island inheritance and variational mode decomposition, and the method comprises the following steps: collecting a vibration signal of a rolling bearing, employing a variational mode decomposition method optimized by a multi-island inheritance algorithm to decompose the vibration signal of the rolling bearing, and obtaining an intrinsic mode component; calculating a sensitive parameter SP of each modal component, selecting two intrinsic modal components with the maximum value of the sensitive parameter SP for reconstruction,and demodulating the reconstructed signal to obtain an envelope spectrum; carrying out signal enhancement on the envelope spectrum by adopting a minimum entropy convolution MOMEDA algorithm to obtainan enhanced envelope spectrum; and identifying rolling bearing fault frequency characteristics according to the enhanced envelope spectrum, and carrying out rolling bearing fault diagnosis. Accordingto the invention, the fault information and noise information of the bearing signal can be effectively separated, the influence of noise on the fault feature extraction precision of the rolling bearing is suppressed, and the fault feature extraction precision of the rolling bearing is greatly improved.

Description

technical field [0001] The invention relates to the technical field of rolling bearing detection, in particular to a bearing fault diagnosis method based on multi-island inheritance and variational mode decomposition. Background technique [0002] Rolling bearings are one of the most commonly used and important components in rotating machinery, and their operating status is directly related to the safe operation of the equipment system. In practical engineering applications, it is more desirable to effectively inspect early faults at the stage of fault occurrence, and to judge the damaged part of the bearing at the early fault stage, so as to provide maintenance decision-making reference for on-site staff. In the early failure stage of rolling bearings, there are often characteristics such as weak impact components and large noise interference from the surrounding environment. This makes it difficult to identify whether the bearing has an early failure on the one hand, and i...

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Problems solved by technology

Rolling bearings in the early failure stage often have the characteristics of weak impact components and large noise interference in the surrounding environment, which makes i

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